Google Analytics 4 Integration Guide

TL;DR

Connect GA4 to Cogny via BigQuery export for unsampled, unlimited analysis of every website event with AI-powered attribution and journey insights.

What you'll accomplish:

Enable BigQuery export in your GA4 property (free for 1M events/day)
Configure daily or streaming data export to BigQuery
Connect BigQuery to Cogny for AI analysis
Access complete event-level data without sampling or API limits

Time required: 10 minutes | Difficulty: Beginner | Prerequisites: GA4 property with data, Google Cloud project

Quick Start: In GA4, navigate to Admin → Property → BigQuery Links → Link → Select your Google Cloud project → Enable daily export.

Related Resources

Maximize your GA4 integration with these complementary guides:

BigQuery Connection Guide - Set up BigQuery access first, then export GA4 data for unsampled analysis
GA4 Event Tracking Configuration - Configure custom events and parameters for deeper behavioral insights
Multi-Touch Attribution Playbook - Use GA4 data to understand the complete customer journey across all touchpoints

Question

How do I connect Google Analytics 4 to Cogny for AI-powered insights?

Answer

Connect GA4 to BigQuery (free, takes 5 minutes). Then connect BigQuery to Cogny.

Cogny's AI analyzes your complete GA4 data—no sampling, no limits.

Quick Tip: GA4's BigQuery export is completely free for up to 1 million events per day. This is more than enough for most businesses. If you haven't set up BigQuery yet, follow our BigQuery Connection Guide first—it takes just 5 minutes and unlocks unsampled data analysis.

Why GA4 Through BigQuery?

The GA4 interface shows you aggregated data. Sampled reports. API limits.

BigQuery gives you:

Every. Single. Event.
Zero sampling.
Unlimited analysis depth.
Custom queries across millions of sessions.

This is what Cogny needs to find insights the GA4 UI will never show you.

What You'll Discover

After connecting GA4:

Attribution insights Which channels actually drive conversions (not just last-click)

User journey analysis Exact paths from first visit to purchase

Cohort behavior How different user segments behave over time

Funnel drop-offs Precisely where users abandon (and why)

Revenue optimization Which campaigns drive highest LTV customers

Note: The GA4 interface limits you to sampled data for large datasets and restricts historical analysis to 14 months. BigQuery export stores unlimited event-level data with zero sampling, enabling deep analysis like cohort tracking, LTV prediction, and custom attribution models that aren't possible in the GA4 UI alone.

Step 1: Enable BigQuery Export in GA4

Log into analytics.google.com

Select your GA4 property.

Click Admin (gear icon, bottom left)

Under Property column, click BigQuery Links

Click Link

Time: 1 minute

Step 2: Choose Google Cloud Project

You'll see "Choose a BigQuery project"

Options:

Use existing project (if you have one)
Create new project (Cogny can help with this)

Select your project.

Don't have a Google Cloud project?

Click "Create a new project" Name it something like company-analytics Google gives you $300 free credits.

Time: 2 minutes (if creating new project)

Step 3: Configure Export Settings

Data location: Choose region closest to you

US: us (multi-region)
EU: eu (multi-region)
Asia: asia-northeast1 (Tokyo) or asia-southeast1 (Singapore)

Export frequency:

✅ Daily (recommended - free)
Streaming (real-time but costs more)

Export type:

✅ Daily export (includes all events)
Fresh daily export (only recent data)

Choose Daily export unless you need real-time data.

Time: 2 minutes

Step 4: Confirm and Link

Click Next

Review settings:

Project ID
Dataset location
Export frequency

Click Submit

GA4 starts exporting.

Important: First export takes 24-48 hours. After that, daily exports arrive every morning (around 9 AM local time).

Time: 1 minute

Step 5: Verify BigQuery Dataset

Go to console.cloud.google.com/bigquery

In the Explorer panel (left side), expand your project.

You should see a new dataset: analytics_PROPERTY_ID

Example: analytics_123456789

Inside, you'll see tables like:

events_20241120 (today's events)
events_20241119 (yesterday's events)
events_YYYYMMDD (one table per day)

Time: 1 minute

Step 6: Connect to Cogny

Now connect this BigQuery dataset to Cogny.

Follow our BigQuery Connection Guide if you haven't already. You'll need to create a service account with read-only access to query your GA4 data.

Steps:

Create service account in Google Cloud
Grant BigQuery Data Viewer permissions
Add JSON key to Cogny
Select the analytics_* dataset

Time: 5 minutes (if you haven't done this yet)

Step 7: Let AI Analyze

Once connected, Cogny's AI:

Catalogs your GA4 schema (2 minutes)
- Identifies all event types
- Maps parameters and user properties
- Builds relationship graph
Analyzes historical data (24 hours)
- User journey patterns
- Conversion paths
- Funnel performance
- Revenue attribution
Generates growth tickets (ongoing)
- Specific optimization opportunities
- Channel reallocation recommendations
- Audience targeting improvements

What's in the GA4 BigQuery Export?

Every table has these fields:

event_date - Date of the event (YYYYMMDD format) event_timestamp - Precise microsecond timestamp event_name - Event type (page_view, purchase, etc.) user_pseudo_id - Anonymous user identifier user_id - Logged-in user ID (if set)

User properties:

Device category
Operating system
Browser
Geographic location
Traffic source

Event parameters:

Page location
Page title
Revenue
Currency
Item details (for e-commerce)

Custom parameters: Whatever you've configured in GA4 shows up here too.

Example: Finding Your Best Conversion Path

Question you can now answer: "What's the typical journey for customers who spend >$500?"

SQL query Cogny generates:

WITH high_value_users AS (
  SELECT user_pseudo_id
  FROM `project.analytics_123456789.events_*`
  WHERE event_name = 'purchase'
    AND event_value > 500
)
SELECT
  event_name,
  COUNT(*) as event_count,
  AVG(event_timestamp) as avg_time_in_journey
FROM `project.analytics_123456789.events_*`
WHERE user_pseudo_id IN (SELECT user_pseudo_id FROM high_value_users)
GROUP BY event_name
ORDER BY avg_time_in_journey

Result: You see the exact sequence of events that lead to high-value purchases.

Maybe they:

Read blog post
Watch demo video
View pricing
Sign up for trial
Purchase

Now you know what content to create more of.

This type of analysis powers the insights in our funnel optimization guide, where AI identifies exact drop-off points and recommends fixes.

Common Issues

"No data appearing in BigQuery"

GA4 export takes 24-48 hours for first run. After that, data appears daily around 9 AM.

Check back tomorrow.

"Permission denied" when querying

Your service account needs BigQuery Data Viewer role. Go to BigQuery → Dataset → SHARING Add your service account Grant viewer permission

"Dataset not found in Cogny"

Make sure:

BigQuery export is enabled in GA4
At least 24 hours have passed
Service account has access to the dataset

"Events look incomplete"

Check your GA4 setup:

Is GA4 tag installed correctly?
Are events firing properly?
Is Enhanced Measurement enabled?

Use GA4 DebugView to verify events are being collected.

"Costs are higher than expected"

BigQuery charges for data storage and queries.

Typical costs:

Storage: ~$20/month per TB
Queries: ~$5/TB scanned

For most businesses: <$50/month total.

Cogny optimizes queries to minimize costs.

Pro Tips

1. Enable Enhanced Measurement

In GA4: Admin → Data Streams → [Your Stream] → Enhanced Measurement

Turn on:

✅ Page views
✅ Scrolls
✅ Outbound clicks
✅ Site search
✅ Video engagement
✅ File downloads

More events = better AI insights.

2. Set up custom events

Track business-specific actions:

"Start free trial"
"Add to cart"
"Complete onboarding"
"Upgrade to paid"

These events appear in BigQuery automatically.

3. Use User-ID for cross-device tracking

If users log in, set User-ID:

gtag('config', 'G-XXXXXXXXXX', {
  user_id: 'USER_ID_FROM_YOUR_DATABASE'
});

This lets you track the same person across devices.

4. Configure data retention

GA4 UI: 2-14 months maximum BigQuery: Unlimited (you control it)

This is huge for long-term analysis.

5. Partition tables for cost optimization

BigQuery partitions GA4 tables by date automatically. When querying, always include date filter:

WHERE _TABLE_SUFFIX BETWEEN '20241101' AND '20241130'

This scans only November data, not the entire history. Cogny does this automatically.

What You Can Do Now

Immediate actions:

Build attribution report
- See all touchpoints in customer journey
- Understand multi-channel impact
- Optimize budget allocation
Analyze conversion funnels
- Identify exact drop-off points
- See why users abandon
- Get AI recommendations to fix
Segment users by value
- Find characteristics of high-LTV customers
- Target similar audiences
- Stop wasting budget on low-value segments
Track cohort behavior
- Compare user groups over time
- Measure retention improvements
- Predict churn before it happens

Next Steps

Recommended guides:

Combine with other data sources:

The more data sources you connect, the smarter Cogny's AI becomes.

Next Steps

After completing your GA4 BigQuery integration, unlock these advanced capabilities:

Immediate Actions:

Configure custom event tracking to capture business-specific user actions
Connect Google Ads to merge ad performance with website behavior
Review AI-generated funnel analysis to identify conversion bottlenecks

Advanced Analysis:

Build multi-touch attribution models to understand channel contribution
Track cohort behavior to measure retention and user value over time
Set up LTV prediction to identify high-value customer segments early

E-commerce Next Steps:

Connect Shopify or WooCommerce for revenue attribution
Implement server-side tracking for iOS 14+ accuracy
Use CAC analysis to optimize customer acquisition costs

Need help? We're here to assist:

Schedule a GA4 setup review
Join our community for GA4 best practices
Email support@cogny.com with technical questions

FAQ

Q: Does this work with Universal Analytics (old GA)?

No. Only GA4.

Universal Analytics stopped collecting data in July 2023. If you haven't migrated to GA4 yet, do that first.

Q: Can I use this with GA4 + Shopify?

Yes.

GA4 tracks the front-end events. Connect Shopify to BigQuery separately for order data. Cogny merges them automatically.

Q: How much BigQuery storage will I use?

Rough estimate:

Small site (10K sessions/month): ~1 GB/month
Medium site (100K sessions/month): ~10 GB/month
Large site (1M sessions/month): ~100 GB/month

Storage costs $0.02/GB/month. So even a large site costs ~$2/month in storage.

Q: What if I need real-time data?

Enable "Streaming export" in GA4 BigQuery settings. Events appear within minutes instead of next day.

Cost: ~$0.05 per GB streamed. For most sites: $10-50/month.

Q: Can I use the free BigQuery sandbox?

For testing, yes. For production, you need a billing account.

But remember: Google gives $300 free credits. That's enough for months of analysis.

Q: What happens to my historical data?

Only data AFTER you enable BigQuery export is stored. Historical data from before stays in GA4 UI only.

Plan ahead: Enable export now, even if you're not ready to use Cogny yet.

Q: Can I access the raw BigQuery data myself?

Yes!

You own the BigQuery dataset. Query it directly anytime. Cogny doesn't lock you in.

Ready to See AI-Powered GA4 Insights?

Most teams discover they've been over-attributing credit to last-click channels.

Your Facebook ads might be driving awareness. But Google Ads gets the conversion credit.

You've been over-investing in Google, under-investing in Facebook.

The AI finds this in minutes.

Not set up yet?

Schedule a demo and we'll walk you through the entire setup—GA4, BigQuery, and Cogny.

About This Guide

Written by the Cogny team—built by the founders who created AI optimization systems for Netflix, Zalando, and Momondo at Campanja, and scaled growth for Kry, Epidemic Sound, and Yubico through GrowthHackers.se.

We've set up GA4 BigQuery exports for hundreds of companies. This is the battle-tested process.

Last Updated: November 20, 2024

Google Analytics 4 Integration Guide

Google Analytics 4 Integration Guide

TL;DR

Related Resources

Question

Answer

Why GA4 Through BigQuery?

What You'll Discover

Step 1: Enable BigQuery Export in GA4

Step 2: Choose Google Cloud Project

Step 3: Configure Export Settings

Step 4: Confirm and Link

Step 5: Verify BigQuery Dataset

Step 6: Connect to Cogny

Step 7: Let AI Analyze

What's in the GA4 BigQuery Export?

Example: Finding Your Best Conversion Path

Common Issues

Pro Tips

What You Can Do Now

Next Steps

Next Steps

FAQ

Ready to See AI-Powered GA4 Insights?

See Cogny in Action